An anonymous reader quotes a report from Ars Technica: Just one week after Google's DeepMind AI group finally described its biology efforts in detail, the company is releasing a paper that explains how it analyzed nearly every protein encoded in the human genome and predicted its likely three-dimensional structure -- a structure that can be critical for understanding disease and designing treatments. In the very near future, all of these structures will be released under a Creative Commons license via the European Bioinformatics Institute, which already hosts a major database of protein structures. In a press conference associated with the paper's release, DeepMind's Demis Hassabis made clear that the company isn't stopping there. In addition to the work described in the paper, the company will release structural predictions for the genomes of 20 major research organisms, from yeast to fruit flies to mice. In total, the database launch will include roughly 350,000 protein structures.
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At some point in the near future (possibly by the time you read this), all this data will be available on a dedicated website hosted by the European Bioinformatics Institute, a European Union-funded organization that describes itself in part as follows: "We make the world's public biological data freely available to the scientific community via a range of services and tools." The AlphaFold data will be no exception; once the above link is live, anyone can use it to download information on the human protein of their choice. Or, as mentioned above, the mouse, yeast, or fruit fly version. The 20 organisms that will see their data released are also just a start. DeepMind's Demis Hassabis said that over the next few months, the team will target every gene sequence available in DNA databases. By the time this work is done, over 100 million proteins should have predicted structures. Hassabis wrapped up his part of the announcement by saying, "We think this is the most significant contribution AI has made to science to date." It would be difficult to argue otherwise. Further reading: Google details its protein-folding software, academics offer an alternative (Ars Technica)

Last year the artificial intelligence group DeepMind cracked a mystery that has flummoxed scientists for decades: stripping bare the structure of proteins, the building blocks of life. Now, having amassed a database of nearly all human protein structures, the company is making the resource available online free for researchers to use. From a report: The key to understanding our basic biological machinery is its architecture. The chains of amino acids that comprise proteins twist and turn to make the most confounding of 3D shapes. It is this elaborate form that explains protein function; from enzymes that are crucial to metabolism to antibodies that fight infectious attacks. Despite years of onerous and expensive lab work that began in the 1950s, scientists have only decoded the structure of a fraction of human proteins.

DeepMind's AI program, AlphaFold, has predicted the structure of nearly all 20,000 proteins expressed by humans. In an independent benchmark test that compared predictions to known structures, the system was able to predict the shape of a protein to a good standard 95% of time. DeepMind, which has partnered with the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), hopes the database will help researchers to analyse how life works at an atomic scale by unpacking the apparatus that drives some diseases, make strides in the field of personalised medicine, create more nutritious crops and develop "green enzymes" that can break down plastic.

UnknowingFool shares a report from CBS News: After being down for a month due to a computer issue, Hubble was brought back up last week. NASA released images captured by Hubble over the weekend including a rare observance of two galaxies that are colliding. The other interesting image is that of a spiral galaxy with three arms, as most spiral galaxies have an even number of arms. "I'm thrilled to see that Hubble has its eye back on the universe, once again capturing the kind of images that have intrigued and inspired us for decades," NASA administrator Bill Nelson said in a statement. "This is a moment to celebrate the success of a team truly dedicated to the mission. Through their efforts, Hubble will continue its 32nd year of discovery, and we will continue to learn from the observatory's transformational vision."

turp182 shares a report from USA Today: [T]he UAE is now testing a new method that has drones fly into clouds to give them an electric shock to trigger rain production [...]. The project is getting renewed interest after the UAE's National Center of Meteorology recently published a series of videos on Instagram of heavy rain in parts of the country. Water gushed past trees, and cars drove on rain-soaked roads. The videos were accompanied by radar images of clouds tagged "#cloudseeding." The Independent reports recent rain is part of the drone cloud seeding project.

The UAE oversaw more than 200 cloud seeding operations in the first half of 2020, successfully creating excess rainfall, the National News reported. There have been successes in the U.S., as well as China, India, and Thailand. Long-term cloud seeding in the mountains of Nevada have increased snowpack by 10% or more each year, according to research published by the American Meteorological Society. A 10-year cloud seeding experiment in Wyoming resulted in 5-10% increases in snowpack, according to the State of Wyoming. According to a researcher that worked on the drone initiative, "the aim of the UAE's project is to change the balance of electrical charge on the cloud droplets, causing water droplets to clump together and fall as rain when they are big enough."